Japan researchers harness quantum entanglement to boost robot posture control.
Explore how researchers are using quantum computing to enhance the movement of robots, making them more efficient and smooth.
Category: robotics/AI – Page 11
Japan trials giant robot hand to scoop buried items at quake sites
Japan trials giant robot hand on excavator to scoop earthquake rubble.
Japanese researchers unveiled a disaster recovery robot hand and drilling AI capable of handling fragile objects and digging buried debris.
Why Meta Just Froze AI Hiring & What It Really Means
Questions to inspire discussion.
đ Q: How often do these extreme job offers occur in the tech industry? A: These hundred-million-dollar job offers are rare occurrences and not representative of typical hiring practices in the tech industry, even during boom cycles.
đ Q: What does Metaâs hiring freeze suggest about the AI industry? A: Metaâs sudden shift from aggressive hiring to a freeze may indicate a potential cooling in the AI sector or a strategic reassessment of their AI investments and talent needs.
Strategic Considerations for Companies.
đą Q: Why are big tech companies making such large offers for AI talent? A: Large tech companies are making enormous offers to secure top AI talent due to perceived strategic vulnerability and the fear of falling behind in a rapidly evolving technological landscape.
đ Q: What should companies consider when competing for AI talent? A: Companies should evaluate the long-term sustainability of offering extreme compensation packages and consider the potential market shifts that could affect the value of AI talent investments.
Tokyo releases AI-generated video of Mount Fuji erupting
With Mount Fuji 100 kilometers away, the video from the Tokyo Metropolitan Government aims to inform Tokyoites about how an eruption could still seriously impact their lives.
Digital to analog in one smooth step: Device could replace signal modulators in fiber-optic networks
Addressing a major roadblock in next-generation photonic computing and signal processing systems, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a device that can bridge digital electronic signals and analog light signals in one fluid step.
Built on chips made out of lithium niobate, the workhorse material of optoelectronics, the new device offers a potential replacement for the ubiquitous but energy-intensive digital-to-analog conversion and electro-optic modulation systems used all over todayâs high-speed data networks.
âOptical communication and high-performance computing, including large language models, relies on conversion of massive amounts of data between the electrical domainâused for storage and computationâand the optical domain used for data transfer,â said senior author Marko LonÄar, the Tiantsai Lin Professor of Electrical Engineering at SEAS.
The Non-Singular Singularity
Part 1 of the Singularity Series was âPutting Brakes on the Singularity.â That essay looked at how economic and other non-technical factors will slow down the practical effects of AI, and we should question the supposedly immediate move from AGI to SAI (superintelligent AI).
In part 3, I will consider past singularities, different paces for singularities, and the difference between intelligence and speed accelerations.
In part 4, I will follow up by offering alternative models of AI-driven progress.
What comes after agentic AI? This powerful new technology will change everything
Ten years from now, it will be clear that the primary ways we use generative AI circa 2025ârapidly crafting content based on simple instructions and open-ended interactionsâwere merely building blocks of a technology that will increasingly be built into far more impactful forms.
The real economic effect will come as different modes of generative AI are combined with traditional software logic to drive expensive activities like project management, medical diagnosis, and insurance claims processing in increasingly automated ways.
In my consulting work helping the worldâs largest companies design and implement AI solutions, Iâm finding that most organizations are still struggling to get substantial value from generative AI applications. As impressive and satisfying as they are, their inherent unpredictability makes it difficult to integrate into the kind of highly standardized business processes that drive the economy.
A look at the next big iteration of the transformative technology.